1. An Introduction to Scala
Blending OO and Functional Paradigms
Miles Sabin, Chuusai Ltd.
http://www.chuusai.com/
http://uk.linkedin.com/in/milessabin
http://twitter.com/milessabin

2. Outline
●
Background
●
Functional Features
●
Object-Oriented Features
●
Selected Highlights
●
Tools and Frameworks
●
Roadmap

3. Background
●
Designed by Martin Odersky (Pizza, GJ and
Java 5) of EPFL as the successor to Funnel
●
Objectives,
●
Blend object-oriented and functional styles
●
Seamless interoperability with Java (and .Net?)
●
Project started in 2003
●
First public release in 2004
●
Currently at 2.7.7
●
2.8 release due very soon

4. Scala is the Future of Java
●
Scala can be thought of as a superset of
current Java
●
It has all the object-oriented features of
current Java (some in a slightly different and
improved form)
●
It already has many of the most desirable
proposed extensions to Java (eg. true closures)
●
Nevertheless, it compiles to Java bytecode
●
Flawless interopability with Java, leverages the
mature Hotspot JIT

5. Interoperbility with Java
●
There are many alternative JVM languages.
Some also strongly “Java-compatible”
●
Close source and binary mapping to Java
– Scala, Groovy, JavaFX, AspectJ
●
This holds out the prospect that most Java
tools, libraries and frameworks will Just
Work, or work with only minor adaptation
●
Additional promise of gradual migration of
existing Java projects

6. Who's Using It?
●
A rapidly growing list of companies and
projects,
●
Twitter (infrastructure)
●
LinkedIn (analytics, infrastructure)
●
EDF Trading (analytics, infrastructure)
●
Sony Pictures Imageworks (infrastructure)
●
SAP/Siemens (ESME, enterprise messaging)
●
Novell (Pulse, enterprise messaging)

7. Why Mix OO and FP?
●
Each has complementary strengths —
●
OO provides excellent support for,
– Subtyping and inheritance
– Modular components
– Classes as partial abstractions
●
FP provides excellent support for,
– Higher order functions
– ADTs, structural recursion and pattern matching
– Parametric polymorphism
●
They've been converging for a while now

8. Scala has a REPL
●
Common in scripting and functional
languages
●
Great for exploratory programming
●
We'll be using it as we go along

9. Scala Cleans Up Java Syntax
●
Semi-colons are optional, equals is ==
●
All statements are expressions and have a
value
●
Type inference eliminates the most
annoying explicit typing annotations
●
Case-classes have minimal boilerplate
●
Closures and by name arguments allow
libraries to define specialized control
structures

10. Statically Typed with Inference
●
All definitions must have a static type
val m : Map[Int, String]
●
However these types are typically inferred
scala> val m = Map(1 -> "one", 2 -> "two")
m : Map[Int, String] = Map(1 -> one, 2 -> two)
●
Method return types are also inferred
scala> def twice(i : Int) = i*2
twice: (i: Int)Int
Argument types must be explicit, also the
return types for recursive functions

11. First-Class Functions
●
Scala allows the definition of functions
def plusOne(x : Int) = x+1
●
Functions can be arguments and results
def applyTwice(x : Int, f : Int => Int) = f(f(x))
applyTwice(3, plusOne) // == 5
●
Can be anonymous and close over their
environment
def twice(f : Int => Int) = (x : Int) => f(f(x))
twice(plusOne)(3) // == 5
●
Function literal syntax is concise
twice(_+1)(3) // == 5

12. Higher-Order Functions
●
Higher-order functions are used
extensively in Scala's standard library
List(1, 2, 3).map(_*2) // == List(2, 4, 6)
List(1, 2, 3, 4).find(_%2 == 0) // Some(2)
List(1, 2, 3, 4).filter(_%2 == 0) // List(2, 4)
def recip(x : Int) = if(x == 0) None else Some(1.0/x)
scala> List(0, 1, 2, 3).flatMap(recip)
res0: List[Int] = List(1.0, 0.5, 0.3333333333333333)

13. For Comprehensions
●
Scala's “for comprehensions” capture
common patterns of use of map, flatMap
and filter
val l1 = List(0, 1)
val l2 = List(2, 3)
scala> for (x <- l1; y <- l2) yield (x, y)
res0: List[(Int, Int)] = List((0,2), (0,3), (1,2), (1,3))
The for expression desugars to,
l.flatMap(x => l2.map(y => (x, y))
●
These patterns are the monad laws for the
subject type

14. Case Classes are Lightweight
●
Eliminate a lot of the boilerplate associated
with Java implementations of simple data
types
public class User {
private final String name;
private final String pass;
public User(String name_, String pass_) {
name = name_;
pass = pass_;
}
public boolean equals(Object other) {
// Stuff ...
}
public int hashCode() {
// More stuff ...
}
}

15. Case Classes are Lightweight
●
The Scala equivalent
case class User(name : String, pass : String)
●
Accessors, equals, hashCode and toString
are provided automatically
●
“new” is optional
val joe = User("Joe Bloggs", "<secret>")
●
“Copy with changes” supports immutable
functional objects
val joeUpdated = joe.copy(pass = "<still secret>")

16. Pattern Matching
●
Case classes model ADTs from functional
languages and support pattern matching
sealed trait Tree[T]
case class Leaf[T](elem : T) extends Tree[T]
case class Node[T](left : Tree[T], right : Tree[T])
val t = Node(Node(Leaf("bar"), Leaf("baz")), Leaf("foo"))
def find[T](tree : Tree[T], elem : T) : Boolean =
tree match {
case Node(l, r) => find(l, elem) || find(r, elem)
case Leaf(`elem`) => true
case _ => false
}
●
Matching is the inverse of construction

17. The Option Type
●
“Null References: The Billion Dollar
Mistake” — Tony Hoare
●
Scala provides a safe alternative
scala> List(1, 2, 3) find (_ == 2)
res0: Option[Int] = Some(2)
scala> List(1, 2, 3) find (_ == 4)
res0: Option[Int] = None
●
Option interacts nicely with matching
List(1, 2, 3) find (_ == 2) match {
case Some(i) => println("Found "+i)
case None => println("Not found")
}

18. For Comprehensions Again
●
Option implements map, flatMap and Filter
so works nicely with for comprehensions
def goodPair(x : Int, y : Int) =
for(fst <- recip(x); snd <- recip(y))
yield (x, y)
scala> goodPair(1, 2)
res0: Option[(Int, Int)] = Some((1,2))
scala> goodPair(1, 0)
res0: Option[(Int, Int)] = None
●
Using Option rather than null has clear
benefits when used in this way

19. Tools and Frameworks
●
Most Java tools and frameworks work with
Scala Out Of The Box
●
Testing frameworks —
●
Specs, ScalaTest, ScalaCheck
●
Web frameworks —
●
Lift
●
Wicket and Play recently added Scala support
●
IDE support — the big three (Eclipse,
Netbeans, IDEA) all actively developed

20. Roadmap
●
Upcoming releases,
●
Beta of 2.8 now available
●
First 2.8 Release Candidate expected in March
●
2.8 Final expected June/July
●
Subsequent 2.8-series releases will
continue current exploratory work,
●
Type specialization (still needs library support)
●
Continuations (currently a compiler plugin)
●
Linear/immutable/non-null types

21. Find Out More
●
Scala's home at EPFL
http://www.scala-lang.org
●
See also the scala and scala-user mailing list
●
The London Scala Users' Group
http://www.meetup.com/london-scala
●
Publications
●
Programming in Scala
Odersky, Venners and Spoon
●
Programming in Scala
Wampler and Payne

22. An Introduction to Scala
Blending OO and Functional Paradigms
Miles Sabin, Chuusai Ltd.
http://www.chuusai.com/
http://uk.linkedin.com/in/milessabin
http://twitter.com/milessabin